Field of the Invention
The present invention relates generally to the measurement of a neural response evoked by electrical stimulation and, more particularly, to the automatic measurement of an evoked neural response.
Related Art
Hearing loss, which may be due to many different causes, is generally of two types, conductive and sensorineural. In some cases, a person may have hearing loss of both types. Conductive hearing loss occurs when the normal mechanical pathways for sound to reach the hair cells in the cochlea are impeded, for example, by damage to the ossicles. Conductive hearing loss is often addressed with conventional auditory prostheses commonly referred to as hearing aids, which amplify sound so that acoustic information can reach the cochlea.
In many people who are profoundly deaf, however, the reason for their deafness is sensorineural hearing loss. This type of hearing loss is due to the absence or destruction of the hair cells in the cochlea which transduce acoustic signals into nerve impulses. Those suffering from sensorineural hearing loss are thus unable to derive suitable benefit from conventional hearing aids due to the damage to or absence of the mechanism for naturally generating nerve impulses from sound.
It is for this purpose that another type of auditory prosthesis, a cochlear implant, has been developed. These types of auditory prostheses bypass the hair cells in the cochlea, directly delivering electrical stimulation to the auditory nerve fibers via an implanted electrode assembly. This enables the brain to perceive a hearing sensation resembling the natural hearing sensation normally delivered to the auditory nerve.
Cochlear implants have traditionally comprised an external speech processor unit worn on the body of the recipient and a receiver/stimulator unit implanted in the mastoid bone of the recipient. The external speech processor detects external sound and converts the detected sound into a coded signal through an appropriate speech processing strategy. The coded signal is sent to the implanted receiver/stimulator unit via a transcutaneous link. The receiver/stimulator unit processes the coded signal to generate a series of stimulation sequences which are then applied directly to the auditory nerve via a series-arrangement or an array of electrodes positioned within the cochlea.
More recently, the external speech processor and implanted stimulator unit may be combined to produce a totally implantable cochlear implant capable of operating, at least for a period of time, without the need for an external device. In such an implant, a microphone would be implanted within the body of the recipient, for example in the ear canal or within the stimulator unit. Detected sound is directly processed by a speech processor within the stimulator unit, with the subsequent stimulation signals delivered without the need for any transcutaneous transmission of signals.
Generally, there is a need to obtain data from the implanted components of a cochlear implant. Such data collection enables detection and confirmation of the normal operation of the device, and allows stimulation parameters to be optimized to suit the needs of individual recipients. This includes data relating to the response of the auditory nerve to stimulation, which is of particular relevance to the present invention. Thus, regardless of the particular configuration, cochlear implants generally have the capability to communicate with an external device such as for program upgrades and/or implant interrogation, and to read and/or alter the operating parameters of the device.
Determining the response of an auditory nerve to stimulation has been addressed with limited success in conventional systems. Typically, following the surgical implantation of a cochlear implant, the implant is fitted or customized to conform to the specific recipient demands. This involves the collection and determination of patient-specific parameters such as threshold levels (T levels) and maximum comfort levels (C levels) for each stimulation channel. Essentially, the procedure is performed manually by applying stimulation pulses for each channel and receiving an indication from the implant recipient as to the level and comfort of the resulting sound. For implants with a large number of channels for stimulation, this process is quite time consuming and rather subjective as it relies heavily on the recipient's subjective impression of the stimulation rather than any objective measurement.
This approach is further limited in the case of children and prelingually or congenitally deaf patients who are unable to supply an accurate impression of the resultant hearing sensation, and hence fitting of the implant may be sub-optimal. In such cases an incorrectly-fitted cochlear implant may result in the recipient not receiving optimum benefit from the implant, and in the cases of children, may directly hamper the speech and hearing development of the child. Therefore, there is a need to obtain objective measurements of patient-specific data, especially in cases where an accurate subjective measurement is not possible.
One proposed method of interrogating the performance of an implanted cochlear implant and making objective measurements of patient-specific data such as T and C levels is to directly measure the response of the auditory nerve to an electrical stimulus. The direct measurement of neural responses, commonly referred to as Electrically-evoked Compound Action Potentials (ECAPs) in the context of cochlear implants, provides an objective measurement of the response of the nerves to electrical stimulus. Following electrical stimulation, the neural response is caused by the superposition of single neural responses at the outside of the axon membranes. The measured neural response is transmitted to an externally-located system, typically via a telemetry system. Such Neural Response Telemetry (NRT) provides measurements of the ECAPs from within the cochlea in response to various stimulations. The measurements taken to determine whether a neural response or ECAPs has occurred are referred to herein by the common vernacular NRT measurements. Generally, the neural response resulting from a stimulus presented at one electrode is measured at a neighboring electrode, although this need not be the case.
A sequence 100 of NRT measurements 102 is shown in FIG. 1A. Sequence 100 contains seven NRT measurements 102A-102G which display a good neural response. Each NRT measurement waveform 102A-102G comprises a clear negative peak (N1) 104 and positive peak (P1) 106. Only one positive and negative peak is shown in FIG. 1A for clarity. As used herein, a “good” neural response is one which approximates a true neural response to an applied stimulus current.
An NRT measurement waveform may have a partial N1 peak, no P1 peak or a double positive peak P1 and P2 and still represent a good neural response. The measurement waveforms 102 toward the top of the graph depicted in FIG. 1A (measurement waveforms 102A, 102B, for example) indicates a stronger neural response to a relatively large neural stimulus, while the measurement waveforms toward the bottom of the graph (measurement waveforms 102F and 102G, for example) indicate a weaker neural response with reduced neural stimuli strengths.
Two sequences 120A and 120B of seven (7) NRT measurements 122A-122G that display the absence of a neural response are shown in FIG. 1B. In the left-hand sequence 120A, stimulus artifact and/or noise are observed. The stimulus artifact may give the impression of artificial peaks which may be interpreted as a neural response to a previously applied stimulus signal. In right-hand sequence 120B, noise is observed.
Distinguishing between measurements that display a neural response such as those of FIG. 1A, and measurements which do not display a neural response such as those of FIG. 1B, is an important aspect of performing NRT measurements. This task can be extremely difficult, for instance when the combination of stimulus artifact and noise gives the appearance of a weak neural response.
In particular, the minimum stimulus current level required to evoke a neural response at a given electrode is referred to herein as the threshold NRT level, or T-NRT. In general, T-NRT profiles are correlated with MAP T and C profiles, and thus T-NRT levels can be used as a guide for MAP fitting. Accordingly, accurate determination of T-NRT values for each electrode and for each recipient is highly desirable.
One conventional approach to determine T-NRT values is the Amplitude Growth Function (AGF) method. The AGF method is based on the premise that the peak-to-peak amplitude of a neural response increases linearly with stimulus current level. It should be appreciated, however, that the relationship is more accurately defined by a sigmoidal function. By obtaining the value at different stimulus current levels, a regression line may be drawn through these measurement points and extrapolated to the point at which the peak-to-peak amplitude becomes zero, thus indicating the threshold stimulus level.
For example, FIG. 2 illustrates a typical, non-linear, measurement set of peak-to-peak amplitude (in microvolts) vs. current level (in digitized current level units). As is well known in the art, there is a one-to-one exponential relationship between the unit of current level and the conventional unit of current (the ampere). In one embodiment, the current level scale is from 0 to 255 with each unit representing an increasingly lager quantity of amperes. This single set of measurements 200 (only one of which is referenced in FIG. 2 for ease of illustration) can be fitted with a number of regression lines 202A, 202B, and 202C, yielding possible T-NRT values of 125, 135 and 148 current level units, a variation of over 18%. This is because AGF is observer-dependent when selecting the measurement points to include in regression.
In addition, the AGF approach requires a significant number of NRT measurements above the threshold to enable a regression line to be determined. Such measurements may be beyond the recipient's loudest acceptable or comfort level, and thus the ability to postoperatively obtain such measurements is limited. Additionally, such measurements do not yield a simple linear relationship, and typically various regression lines can be determined resulting in significantly different T-NRT levels from a given measurement set.
Visual detection of T-NRT levels is a more fundamental conventional approach. NRT measurements of increasing stimulus level are performed until the stimulus level at which a neural response is detected, at which point the T-NRT level is defined as the stimulus level. Visual detection depends critically on the acuity of the observer to distinguish between neural responses and artifact or noise. Visual detection of threshold is also observer-dependent.
The presence of stimulus artifacts and noise in measurements of an evoked neural response can lead to an incorrect determination of whether a neural response, or ECAP, has occurred in the above conventional systems. Accordingly, there is a need to objectively and accurately detect T-NRT thresholds to facilitate neural response determinations.
Indeed, there is a need to accurately measure the response of nerves to electrical stimulation in stimulating medical devices that deliver electrical stimulation to other neural regions of a recipient such as the central nervous system (including the brain and spinal cord), as well as the peripheral nervous system (including the autonomic and sensory-somatic nervous systems). Thus, the accurate measurement of a neural response may provide a useful objective measurement of the effectiveness of the stimulation in many applications.